fast-yolo4/3rdparty/opencv/inc/opencv2/face/predict_collector.hpp

/*
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*/

#ifndef __OPENCV_PREDICT_COLLECTOR_HPP__
#define __OPENCV_PREDICT_COLLECTOR_HPP__

#include <vector>
#include <map>
#include <utility>
#include <cfloat>

#include "opencv2/core/base.hpp"

namespace cv {
namespace face {
//! @addtogroup face
//! @{
/** @brief Abstract base class for all strategies of prediction result handling
*/
class CV_EXPORTS_W PredictCollector
{
public:
    virtual ~PredictCollector() {}

    /** @brief Interface method called by face recognizer before results processing
    @param size total size of prediction evaluation that recognizer could perform
    */
    virtual void init(size_t size) { CV_UNUSED(size); }

    /** @brief Interface method called by face recognizer for each result
    @param label current prediction label
    @param dist current prediction distance (confidence)
    */
    virtual bool collect(int label, double dist) = 0;
};

/** @brief Default predict collector

Trace minimal distance with treshhold checking (that is default behavior for most predict logic)
*/
class CV_EXPORTS_W StandardCollector : public PredictCollector
{
public:
    struct PredictResult
    {
        int label;
        double distance;
        PredictResult(int label_ = -1, double distance_ = DBL_MAX) : label(label_), distance(distance_) {}
    };
protected:
    double threshold;
    PredictResult minRes;
    std::vector<PredictResult> data;
public:
    /** @brief Constructor
    @param threshold_ set threshold
    */
    StandardCollector(double threshold_ = DBL_MAX);
    /** @brief overloaded interface method */
    void init(size_t size) CV_OVERRIDE;
    /** @brief overloaded interface method */
    bool collect(int label, double dist) CV_OVERRIDE;
    /** @brief Returns label with minimal distance */
    CV_WRAP int getMinLabel() const;
    /** @brief Returns minimal distance value */
    CV_WRAP double getMinDist() const;
    /** @brief Return results as vector
    @param sorted If set, results will be sorted by distance
    Each values is a pair of label and distance.
    */
    CV_WRAP std::vector< std::pair<int, double> > getResults(bool sorted = false) const;
    /** @brief Return results as map
    Labels are keys, values are minimal distances
    */
    std::map<int, double> getResultsMap() const;
    /** @brief Static constructor
    @param threshold set threshold
    */
    CV_WRAP static Ptr<StandardCollector> create(double threshold = DBL_MAX);
};

//! @}
}
}

#endif